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Sakana AI introduces PC-ALM, a local-learning alternative to backpropagation that enables training of 1000-layer neural networks using only local dynamics.
Introduces Score Broadcast and Decorrelation (SBD), a principled framework for broadcast-based credit assignment that generalizes to differentiable loss families including cross-entropy, Bregman divergences, and proper scoring rules. The work provides theoretical grounding for the three-factor learning rule and demonstrates improved performance over existing broadcast approaches on CIFAR-10 and Tiny ImageNet.